Notes

Identifying the result of aging, time to recover, as well as post-stroke memantine treatment method in overdue thalamic gliosis right after cortical infarct.
Information on microbiological and susceptibility profiles of clinical isolates in Mongolia is scarce, hampering infection control and clinical care.

Species and resistance profiles of 6334 clinical gram negative isolates, collected at Mongolia's National Center for Maternal and Child Health between 2014 and 2017 were analyzed.

Annual proportion of multidrug-resistance among
and
isolates increased from 2.8% to 16.6% and 3.5% to 22.6% respectively;
isolates exhibiting susceptibilities suggestive of extended spectrum beta-lactamase (ESBL) production from 73% to 94%. By 2017, 60.6% of
isolates were multidrug-resistant, most originated from intensive care wards. Enterobacteriaceae exhibiting susceptibility patterns suggestive of ESBL production and multidrug-resistant organisms were common and their incidence increased rapidly.

These findings will serve to build strategies to strengthen microbiological surveillance, diagnostics and infection control; and to develop empiric therapy and stewardship recommendations for Mongolia's largest Children's and Maternity hospital.
These findings will serve to build strategies to strengthen microbiological surveillance, diagnostics and infection control; and to develop empiric therapy and stewardship recommendations for Mongolia's largest Children's and Maternity hospital.
Over the past decade, the incidence of human immunodeficiency virus (HIV) infections in Tajikistan increased significantly, with women particularly vulnerable to acquiring HIV. This research assessed individual determinants associated with HIV testing among women of reproductive age.

Secondary data analysis was done using data from 5,867 females aged 15-49 years. Chi-square test, t-test, and multivariate analysis were applied to find associations between women's socio-demographic characteristics, reproductive health variables, and HIV testing uptake.

Overall, only 26% (1,501) of women in the present research reported HIV testing in the past. Multiple regression indicated that HIV testing was significantly associated with participants' age (25-34 age group OR 0.7, p ≤ 0.001; 35-49 age group OR 0.2, p ≤ 0.001), education (OR 2.2, p ≤ 0.001), area of residence (OR 0.6, p ≤ 0.001), marital status (OR 2.4, p ≤ 0.001), HIV knowledge (OR 1.1, p ≤ 0.001), and pregnancy history (OR 6.7, p ≤ 0.001).

Results of this research suggest that there is a need for culturally acceptable interventions, including outreach to increase the overall HIV testing rate among women in Tajikistan.
Results of this research suggest that there is a need for culturally acceptable interventions, including outreach to increase the overall HIV testing rate among women in Tajikistan.
Although South Asians are considered to be at high risk for cardiovascular diseases, research evidence on the health impacts of physical activity (PA) remains very limited. In this study we aimed to explore the patterns of PA and to investigate whether engaging in regular PA is associated with better Self-Rated Health (SRH) among South Asians.

Cross-sectional data on population health were drawn from the World Health Survey of WHO. Subjects were 28,020 male and female South Asians (from Bangladesh, India, Nepal, and Sri Lanka) aged 18 years and above. Data were analysed using descriptive and multivariable logistic regression analyses.

The proportion of the sample population reported good SRH was 44.3%, 58.7%, 37.7%, and 73.7% in Bangladeshis, Indians, Nepalese, and Sri Lankans, respectively. Regular engagement in moderate PA was highest in Nepal (69.7%) and lowest in Bangladesh (37.4%). Vigorous PA was highest in India (29.9%) and lowest in Bangladesh (17.9%). In Bangladesh, compared to those never engaged in MPA, those who engaged for 1-2, 3-4, 5-6, or 7 days a week were 30% [AOR=1.306; 95%CI 1.085-1.572], 33% [AOR=1.326; 95%CI 1.093-1.609], 39% [AOR=1.389; 95%CI 1.125-1.716], and 46% [AOR=1.459; 95%CI 1.249-1.705] more likely to report being in good health, respectively.

We found that self-reported engagement in physical activities varies in South Asian countries. Since engaging in PA may help improve subjective and objective health status, health policy makers need to focus on designing exercise-friendly neighbourhoods in an attempt to promote population health.
We found that self-reported engagement in physical activities varies in South Asian countries. Since engaging in PA may help improve subjective and objective health status, health policy makers need to focus on designing exercise-friendly neighbourhoods in an attempt to promote population health.
To develop and compare deep learning (DL) algorithms to detect keratoconus on the basis of corneal topography and validate with visualization methods.

We retrospectively collected corneal topographies of the study group with clinically manifested keratoconus and the control group with regular astigmatism. All images were divided into training and test datasets. We adopted three convolutional neural network (CNN) models for learning. The test dataset was applied to analyze the performance of the three models. In addition, for better discrimination and understanding, we displayed the pixel-wise discriminative features and class-discriminative heat map of diopter images for visualization.

Overall, 170 keratoconus, 28 subclinical keratoconus and 156 normal topographic pictures were collected. The convergence of accuracy and loss for the training and test datasets after training revealed no overfitting in all three CNN models. The sensitivity and specificity of all CNN models were over 0.90, and the area under the receiver operating characteristic curve reached 0.995 in the ResNet152 model. The pixel-wise discriminative features and the heat map of the prediction layer in the VGG16 model both revealed it focused on the largest gradient difference of topographic maps, which was corresponding to the diagnostic clues of ophthalmologists. The subclinical keratoconus was positively predicted with our model and also correlated with topographic indexes.

The DL models had fair accuracy for keratoconus screening based on corneal topographic images. Etanercept The visualization mentioned in the current study revealed that the model focused on the appropriate region for diagnosis and rendered clinical explainability of deep learning more acceptable.

These high accuracy CNN models can aid ophthalmologists in keratoconus screening with color-coded corneal topography maps.
These high accuracy CNN models can aid ophthalmologists in keratoconus screening with color-coded corneal topography maps.
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